Storing a Data Object as Data Regions in a Storage Network

ABSTRACT

A method for execution by a computing device of a storage network begins by receiving a write request for a data object, determining a plurality of data regions for the data object, determining storage identification information for each data region of the plurality of data regions and generating a storage table for the data object that includes information sufficient to identify each data region of the plurality of data regions. For a first data region of the plurality of data regions the method continues by dividing the first data region into a plurality of data segments, and dispersed error encoding the plurality of data segments to produce a plurality of sets of encoded data slices. The method then continues by sending a write request for each encoded data slice of each set of encoded data slices of the plurality of sets of encoded data slices to the storage network, and when at least a write threshold number of write responses is received for each of the plurality of sets of encoded data slices the method ends by updating the storage table to indicate that the first data region is available for retrieval.

CROSS REFERENCE TO RELATED APPLICATIONS

The present U.S. Utility Patent application claims priority pursuant to35 U.S.C. § 120 as a continuation of U.S. Utility application Ser. No.16/806,123, entitled “WRITE RESPONSE THRESHOLDS”, filed Mar. 2, 2020,which is a continuation of U.S. Utility application Ser. No. 15/816,934,entitled “IMPATIENT WRITES”, filed Nov. 17, 2017, issued as U.S. Pat.No. 10,587,691 on Mar. 2, 2020, which is a continuation-in-part of U.S.Utility application Ser. No. 15/216,494, entitled “UTILIZING DATA OBJECTSTORAGE TRACKING IN A DISPERSED STORAGE NETWORK”, filed Jul. 21, 2016,issued as U.S. Pat. No. 10,334,046 on Jun. 25, 2019, which is acontinuation of U.S. Utility application Ser. No. 14/056,015, entitled“UTILIZING DATA OBJECT STORAGE TRACKING IN A DISPERSED STORAGE NETWORK”,filed Oct. 17, 2013, issued as U.S. Pat. No. 9,521,197 on Dec. 13, 2016,which claims priority pursuant to 35 U.S.C. § 119(e) to U.S. ProvisionalApplication No. 61/733,698, entitled “ACCESSING DATA UTILIZING A REGIONHEADER OBJECT”, filed Dec. 5, 2012, all of which are hereby incorporatedherein by reference in their entirety and made part of the present U.S.Utility Patent Application for all purposes.

STATEMENT REGARDING FEDERALLY SPONSORED RESEARCH OR DEVELOPMENT

Not Applicable.

INCORPORATION-BY-REFERENCE OF MATERIAL SUBMITTED ON A COMPACT DISC

Not Applicable.

BACKGROUND OF THE INVENTION Technical Field of the Invention

This invention relates generally to computer networks, and moreparticularly to dispersed or cloud storage.

Description of Related Art

Computing devices are known to communicate data, process data, and/orstore data. Such computing devices range from wireless smart phones,laptops, tablets, personal computers (PC), work stations, and video gamedevices, to data centers that support millions of web searches, stocktrades, or on-line purchases every day. In general, a computing deviceincludes a central processing unit (CPU), a memory system, userinput/output interfaces, peripheral device interfaces, and aninterconnecting bus structure.

As is further known, a computer may effectively extend its CPU by using“cloud computing” to perform one or more computing functions (e.g., aservice, an application, an algorithm, an arithmetic logic function,etc.) on behalf of the computer. Further, for large services,applications, and/or functions, cloud computing may be performed bymultiple cloud computing resources in a distributed manner to improvethe response time for completion of the service, application, and/orfunction. For example, Hadoop is an open source software framework thatsupports distributed applications enabling application execution bythousands of computers.

In addition to cloud computing, a computer may use “cloud storage” aspart of its memory system. As is known, cloud storage enables a user,via its computer, to store files, applications, etc. on a remote orInternet storage system. The remote or Internet storage system mayinclude a RAID (redundant array of independent disks) system and/or adispersed storage system that uses an error correction scheme to encodedata for storage.

In a RAID system, a RAID controller adds parity data to the originaldata before storing it across an array of disks. The parity data iscalculated from the original data such that the failure of a single disktypically will not result in the loss of the original data. While RAIDsystems can address certain memory device failures, these systems maysuffer from effectiveness, efficiency and security issues. For instance,as more disks are added to the array, the probability of a disk failurerises, which may increase maintenance costs. When a disk fails, forexample, it needs to be manually replaced before another disk(s) failsand the data stored in the RAID system is lost. To reduce the risk ofdata loss, data on a RAID device is often copied to one or more otherRAID devices. While this may reduce the possibility of data loss, italso raises security issues since multiple copies of data may beavailable, thereby increasing the chances of unauthorized access. Inaddition, co-location of some RAID devices may result in a risk of acomplete data loss in the event of a natural disaster, fire, powersurge/outage, etc.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWING(S)

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) in accordance with the presentdisclosure;

FIG. 2 is a schematic block diagram of an embodiment of a computing corein accordance with the present disclosure;

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data in accordance with the present disclosure;

FIG. 4 is a schematic block diagram of a generic example of an errorencoding function in accordance with the present disclosure;

FIG. 5 is a schematic block diagram of a specific example of an errorencoding function in accordance with the present disclosure;

FIG. 6 is a schematic block diagram of an example of slice naminginformation for an encoded data slice (EDS) in accordance with thepresent disclosure;

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of data in accordance with the present disclosure;

FIG. 8 is a schematic block diagram of a generic example of an errordecoding function in accordance with the present disclosure;

FIG. 9 is a schematic block diagram of an example of a dispersed storagenetwork in accordance with the present disclosure;

FIG. 10A is a schematic block diagram of another embodiment of a DSN inaccordance with the present disclosure; and

FIG. 10B is a flowchart illustrating an example of writing data in a DSNin accordance with the present disclosure.

DETAILED DESCRIPTION OF THE INVENTION

FIG. 1 is a schematic block diagram of an embodiment of a dispersed, ordistributed, storage network (DSN) 10 that includes a plurality ofdispersed storage (DS) computing devices or processing units 12-16, a DSmanaging unit 18, a DS integrity processing unit 20, and a DSN memory22. The components of the DSN 10 are coupled to a network 24, which mayinclude one or more wireless and/or wire lined communication systems;one or more non-public intranet systems and/or public internet systems;and/or one or more local area networks (LAN) and/or wide area networks(WAN).

The DSN memory 22 includes a plurality of dispersed storage units 36 (DSunits) that may be located at geographically different sites (e.g., onein Chicago, one in Milwaukee, etc.), at a common site, or a combinationthereof. For example, if the DSN memory 22 includes eight dispersedstorage units 36, each storage unit is located at a different site. Asanother example, if the DSN memory 22 includes eight storage units 36,all eight storage units are located at the same site. As yet anotherexample, if the DSN memory 22 includes eight storage units 36, a firstpair of storage units are at a first common site, a second pair ofstorage units are at a second common site, a third pair of storage unitsare at a third common site, and a fourth pair of storage units are at afourth common site. Note that a DSN memory 22 may include more or lessthan eight storage units 36.

DS computing devices 12-16, the managing unit 18, and the integrityprocessing unit 20 include a computing core 26, and network orcommunications interfaces 30-33 which can be part of or external tocomputing core 26. DS computing devices 12-16 may each be a portablecomputing device and/or a fixed computing device. A portable computingdevice may be a social networking device, a gaming device, a cell phone,a smart phone, a digital assistant, a digital music player, a digitalvideo player, a laptop computer, a handheld computer, a tablet, a videogame controller, and/or any other portable device that includes acomputing core. A fixed computing device may be a computer (PC), acomputer server, a cable set-top box, a satellite receiver, a televisionset, a printer, a fax machine, home entertainment equipment, a videogame console, and/or any type of home or office computing equipment.Note that each of the managing unit 18 and the integrity processing unit20 may be separate computing devices, may be a common computing device,and/or may be integrated into one or more of the computing devices 12-16and/or into one or more of the dispersed storage units 36.

Each interface 30, 32, and 33 includes software and/or hardware tosupport one or more communication links via the network 24 indirectlyand/or directly. For example, interface 30 supports a communication link(e.g., wired, wireless, direct, via a LAN, via the network 24, etc.)between computing devices 14 and 16. As another example, interface 32supports communication links (e.g., a wired connection, a wirelessconnection, a LAN connection, and/or any other type of connectionto/from the network 24) between computing devices 12 and 16 and the DSNmemory 22. As yet another example, interface 33 supports a communicationlink for each of the managing unit 18 and the integrity processing unit20 to the network 24.

In general and with respect to DS error encoded data storage andretrieval, the DSN 10 supports three primary operations: storagemanagement, data storage and retrieval. More specifically computingdevices 12 and 16 include a dispersed storage (DS) client module 34,which enables the computing device to dispersed storage error encode anddecode data (e.g., data object 40) as subsequently described withreference to one or more of FIGS. 3-8 . In this example embodiment,computing device 16 functions as a dispersed storage processing agentfor computing device 14. In this role, computing device 16 dispersedstorage error encodes and decodes data on behalf of computing device 14.With the use of dispersed storage error encoding and decoding, the DSN10 is tolerant of a significant number of storage unit failures (thenumber of failures is based on parameters of the dispersed storage errorencoding function) without loss of data and without the need for aredundant or backup copies of the data. Further, the DSN 10 stores datafor an indefinite period of time without data loss and in a securemanner (e.g., the system is very resistant to unauthorized attempts ataccessing or hacking the data).

The second primary function (i.e., distributed data storage andretrieval) begins and ends with a DS computing devices 12-14. Forinstance, if a second type of computing device 14 has data 40 to storein the DSN memory 22, it sends the data 40 to the DS computing device 16via its interface 30. The interface 30 functions to mimic a conventionaloperating system (OS) file system interface (e.g., network file system(NFS), flash file system (FFS), disk file system (DFS), file transferprotocol (FTP), web-based distributed authoring and versioning (WebDAV),etc.) and/or a block memory interface (e.g., small computer systeminterface (SCSI), internet small computer system interface (iSCSI),etc.).

In operation, the managing unit 18 performs DS management services. Forexample, the managing unit 18 establishes distributed data storageparameters (e.g., vault creation, distributed storage parameters,security parameters, billing information, user profile information,etc.) for computing devices 12-16 individually or as part of a group ofuser devices. As a specific example, the managing unit 18 coordinatescreation of a vault (e.g., a virtual memory block associated with aportion of an overall namespace of the DSN) within the DSN memory 22 fora user device, a group of devices, or for public access and establishesper vault dispersed storage (DS) error encoding parameters for a vault.The managing unit 18 facilitates storage of DS error encoding parametersfor each vault by updating registry information of the DSN 10, where theregistry information may be stored in the DSN memory 22, a computingdevice 12-16, the managing unit 18, and/or the integrity processing unit20.

The DS error encoding parameters (e.g., or dispersed storage errorcoding parameters) include data segmenting information (e.g., how manysegments data (e.g., a file, a group of files, a data block, etc.) isdivided into), segment security information (e.g., per segmentencryption, compression, integrity checksum, etc.), error codinginformation (e.g., pillar width, decode threshold, read threshold, writethreshold, etc.), slicing information (e.g., the number of encoded dataslices that will be created for each data segment); and slice securityinformation (e.g., per encoded data slice encryption, compression,integrity checksum, etc.).

The managing unit 18 creates and stores user profile information (e.g.,an access control list (ACL)) in local memory and/or within memory ofthe DSN memory 22. The user profile information includes authenticationinformation, permissions, and/or the security parameters. The securityparameters may include encryption/decryption scheme, one or moreencryption keys, key generation scheme, and/or data encoding/decodingscheme.

The managing unit 18 creates billing information for a particular user,a user group, a vault access, public vault access, etc. For instance,the managing unit 18 tracks the number of times a user accesses anon-public vault and/or public vaults, which can be used to generateper-access billing information. In another instance, the managing unit18 tracks the amount of data stored and/or retrieved by a user deviceand/or a user group, which can be used to generate per-data-amountbilling information.

As another example, the managing unit 18 performs network operations,network administration, and/or network maintenance. Network operationsincludes authenticating user data allocation requests (e.g., read and/orwrite requests), managing creation of vaults, establishingauthentication credentials for user devices, adding/deleting components(e.g., user devices, storage units, and/or computing devices with a DSclient module 34) to/from the DSN 10, and/or establishing authenticationcredentials for the storage units 36. Network operations can furtherinclude monitoring read, write and/or delete communications attempts,which attempts could be in the form of requests. Network administrationincludes monitoring devices and/or units for failures, maintaining vaultinformation, determining device and/or unit activation status,determining device and/or unit loading, and/or determining any othersystem level operation that affects the performance level of the DSN 10.Network maintenance includes facilitating replacing, upgrading,repairing, and/or expanding a device and/or unit of the DSN 10.

To support data storage integrity verification within the DSN 10, theintegrity processing unit 20 (and/or other devices in the DSN 10 such asmanaging unit 18) may assess and perform rebuilding of ‘bad’ or missingencoded data slices. At a high level, the integrity processing unit 20performs rebuilding by periodically attempting to retrieve/list encodeddata slices, and/or slice names of the encoded data slices, from the DSNmemory 22. Retrieved encoded slices are assessed and checked for errorsdue to data corruption, outdated versioning, etc. If a slice includes anerror, it is flagged as a ‘bad’ or ‘corrupt’ slice. Encoded data slicesthat are not received and/or not listed may be flagged as missingslices. Bad and/or missing slices may be subsequently rebuilt usingother retrieved encoded data slices that are deemed to be good slices inorder to produce rebuilt slices. A multi-stage decoding process may beemployed in certain circumstances to recover data even when the numberof valid encoded data slices of a set of encoded data slices is lessthan a relevant decode threshold number. The rebuilt slices may then bewritten to DSN memory 22. Note that the integrity processing unit 20 maybe a separate unit as shown, included in DSN memory 22, included in thecomputing device 16, managing unit 18, stored on a DS unit 36, and/ordistributed among multiple storage units 36.

FIG. 2 is a schematic block diagram of an embodiment of a computing core26 that includes a processing module 50, a memory controller 52, mainmemory 54, a video graphics processing unit 55, an input/output (TO)controller 56, a peripheral component interconnect (PCI) interface 58,an IO interface module 60, at least one IO device interface module 62, aread only memory (ROM) basic input output system (BIOS) 64, and one ormore memory interface modules. The one or more memory interfacemodule(s) includes one or more of a universal serial bus (USB) interfacemodule 66, a host bus adapter (HBA) interface module 68, a networkinterface module 70, a flash interface module 72, a hard drive interfacemodule 74, and a DSN interface module 76.

The DSN interface module 76 functions to mimic a conventional operatingsystem (OS) file system interface (e.g., network file system (NFS),flash file system (FFS), disk file system (DFS), file transfer protocol(FTP), web-based distributed authoring and versioning (WebDAV), etc.)and/or a block memory interface (e.g., small computer system interface(SCSI), internet small computer system interface (iSCSI), etc.). The DSNinterface module 76 and/or the network interface module 70 may functionas one or more of the interface 30-33 of FIG. 1 . Note that the IOdevice interface module 62 and/or the memory interface modules 66-76 maybe collectively or individually referred to as IO ports.

FIG. 3 is a schematic block diagram of an example of dispersed storageerror encoding of data. When a computing device 12 or 16 has data tostore it disperse storage error encodes the data in accordance with adispersed storage error encoding process based on dispersed storageerror encoding parameters. The dispersed storage error encodingparameters include an encoding function (e.g., information dispersalalgorithm, Reed-Solomon, Cauchy Reed-Solomon, systematic encoding,non-systematic encoding, on-line codes, etc.), a data segmentingprotocol (e.g., data segment size, fixed, variable, etc.), and per datasegment encoding values. The per data segment encoding values include atotal, or pillar width, number (T) of encoded data slices per encodingof a data segment (i.e., in a set of encoded data slices); a decodethreshold number (D) of encoded data slices of a set of encoded dataslices that are needed to recover the data segment; a read thresholdnumber (R) of encoded data slices to indicate a number of encoded dataslices per set to be read from storage for decoding of the data segment;and/or a write threshold number (W) to indicate a number of encoded dataslices per set that must be accurately stored before the encoded datasegment is deemed to have been properly stored. The dispersed storageerror encoding parameters may further include slicing information (e.g.,the number of encoded data slices that will be created for each datasegment) and/or slice security information (e.g., per encoded data sliceencryption, compression, integrity checksum, etc.).

In the present example, Cauchy Reed-Solomon has been selected as theencoding function (a generic example is shown in FIG. 4 and a specificexample is shown in FIG. 5 ); the data segmenting protocol is to dividethe data object into fixed sized data segments; and the per data segmentencoding values include: a pillar width of 5, a decode threshold of 3, aread threshold of 4, and a write threshold of 4. In accordance with thedata segmenting protocol, the computing device 12 or 16 divides the data(e.g., a file (e.g., text, video, audio, etc.), a data object, or otherdata arrangement) into a plurality of fixed sized data segments (e.g., 1through Y of a fixed size in range of Kilo-bytes to Tera-bytes or more).The number of data segments created is dependent of the size of the dataand the data segmenting protocol.

The computing device 12 or 16 then disperse storage error encodes a datasegment using the selected encoding function (e.g., Cauchy Reed-Solomon)to produce a set of encoded data slices. FIG. 4 illustrates a genericCauchy Reed-Solomon encoding function, which includes an encoding matrix(EM), a data matrix (DM), and a coded matrix (CM). The size of theencoding matrix (EM) is dependent on the pillar width number (T) and thedecode threshold number (D) of selected per data segment encodingvalues. To produce the data matrix (DM), the data segment is dividedinto a plurality of data blocks and the data blocks are arranged into Dnumber of rows with Z data blocks per row. Note that Z is a function ofthe number of data blocks created from the data segment and the decodethreshold number (D). The coded matrix is produced by matrix multiplyingthe data matrix by the encoding matrix.

FIG. 5 illustrates a specific example of Cauchy Reed-Solomon encodingwith a pillar number (T) of five and decode threshold number of three.In this example, a first data segment is divided into twelve data blocks(D1-D12). The coded matrix includes five rows of coded data blocks,where the first row of X11-X14 corresponds to a first encoded data slice(EDS 1_1), the second row of X21-X24 corresponds to a second encodeddata slice (EDS 2_1), the third row of X31-X34 corresponds to a thirdencoded data slice (EDS 3_1), the fourth row of X41-X44 corresponds to afourth encoded data slice (EDS 4_1), and the fifth row of X51-X54corresponds to a fifth encoded data slice (EDS 5_1). Note that thesecond number of the EDS designation corresponds to the data segmentnumber. In the illustrated example, the value X11=aD1+bD5+cD9,X12=aD2+bD6+cD10, . . . X53=mD3+nD7+oD11, and X54=mD4+nD8+oD12.

Returning to the discussion of FIG. 3 , the computing device alsocreates a slice name (SN) for each encoded data slice (EDS) in the setof encoded data slices. A typical format for a slice name 80 is shown inFIG. 6 . As shown, the slice name (SN) 80 includes a pillar number ofthe encoded data slice (e.g., one of 1-T), a data segment number (e.g.,one of 1-Y), a vault identifier (ID), a data object identifier (ID), andmay further include revision level information of the encoded dataslices. The slice name functions as at least part of a DSN address forthe encoded data slice for storage and retrieval from the DSN memory 22.

As a result of encoding, the computing device 12 or 16 produces aplurality of sets of encoded data slices, which are provided with theirrespective slice names to the storage units for storage. As shown, thefirst set of encoded data slices includes EDS 1_1 through EDS 5_1 andthe first set of slice names includes SN 1_1 through SN 5_1 and the lastset of encoded data slices includes EDS 1_Y through EDS 5_Y and the lastset of slice names includes SN 1_Y through SN 5 Y.

FIG. 7 is a schematic block diagram of an example of dispersed storageerror decoding of a data object that was dispersed storage error encodedand stored in the example of FIG. 4 . In this example, the computingdevice 12 or 16 retrieves from the storage units at least the decodethreshold number of encoded data slices per data segment. As a specificexample, the computing device retrieves a read threshold number ofencoded data slices.

In order to recover a data segment from a decode threshold number ofencoded data slices, the computing device uses a decoding function asshown in FIG. 8 . As shown, the decoding function is essentially aninverse of the encoding function of FIG. 4 . The coded matrix includes adecode threshold number of rows (e.g., three in this example) and thedecoding matrix in an inversion of the encoding matrix that includes thecorresponding rows of the coded matrix. For example, if the coded matrixincludes rows 1, 2, and 4, the encoding matrix is reduced to rows 1, 2,and 4, and then inverted to produce the decoding matrix.

FIG. 9 is a diagram of an example of a dispersed storage network. Thedispersed storage network includes a DS (dispersed storage) clientmodule 34 (which may be in DS computing devices 12 and/or 16 of FIG. 1), a network 24, and a plurality of DS units 36-1 . . . 36-n (which maybe storage units 36 of FIG. 1 and which form at least a portion of DSmemory 22 of FIG. 1 ), a DSN managing unit 18, and a DS integrityverification module (not shown). The DS client module 34 includes anoutbound DS processing section 81 and an inbound DS processing section82. Each of the DS units 36-1 . . . 36-n includes a controller 86, aprocessing module 84 (e.g. computer processor) including acommunications interface for communicating over network 24 (not shown),memory 88, a DT (distributed task) execution module 90, and a DS clientmodule 34.

In an example of operation, the DS client module 34 receives data 92.The data 92 may be of any size and of any content, where, due to thesize (e.g., greater than a few Terabytes), the content (e.g., securedata, etc.), and/or concerns over security and loss of data, distributedstorage of the data is desired. For example, the data 92 may be one ormore digital books, a copy of a company's emails, a large-scale Internetsearch, a video security file, one or more entertainment video files(e.g., television programs, movies, etc.), data files, and/or any otherlarge amount of data (e.g., greater than a few Terabytes).

Within the DS client module 34, the outbound DS processing section 81receives the data 92. The outbound DS processing section 81 processesthe data 92 to produce slice groupings 96. As an example of suchprocessing, the outbound DS processing section 81 partitions the data 92into a plurality of data partitions. For each data partition, theoutbound DS processing section 81 dispersed storage (DS) error encodesthe data partition to produce encoded data slices and groups the encodeddata slices into a slice grouping 96.

The outbound DS processing section 81 then sends, via the network 24,the slice groupings 96 to the DS units 36-1 . . . 36-n of the DSN memory22 of FIG. 1 . For example, the outbound DS processing section 81 sendsslice group 1 to DS storage unit 36-1. As another example, the outboundDS processing section 81 sends slice group #n to DS unit #n.

In one example of operation, the DS client module 34 requests retrievalof stored data within the memory of the DS units 36. In this example,the task 94 is retrieve data stored in the DSN memory 22. Accordingly,and according to one embodiment, the outbound DS processing section 81converts the task 94 into a plurality of partial tasks 98 and sends thepartial tasks 98 to the respective DS storage units 36-1 . . . 36-n.

In response to the partial task 98 of retrieving stored data, a DSstorage unit 36 identifies the corresponding encoded data slices 99 andretrieves them. For example, DS unit #1 receives partial task #1 andretrieves, in response thereto, retrieved slices #1. The DS units 36send their respective retrieved slices 99 to the inbound DS processingsection 82 via the network 24.

The inbound DS processing section 82 converts the retrieved slices 99into data 92. For example, the inbound DS processing section 82de-groups the retrieved slices 99 to produce encoded slices per datapartition. The inbound DS processing section 82 then DS error decodesthe encoded slices per data partition to produce data partitions. Theinbound DS processing section 82 de-partitions the data partitions torecapture the data 92.

In one example of operation, the DSN of FIGS. 1 and 9 can be used toimpatiently write encoded data slices to DS units. Examples of anapparatus and method for impatiently writing encoded data slices are setout below in conjunction with FIGS. 10A and 10B respectively. Whiledescribed in the context of functionality provided by DS processing unit16, this functionality may be implemented utilizing any module and/orunit of a dispersed storage network (DSN), alone or in combination,including one or more of DS units 36-1 . . . 36-n, DS Managing Unit 18and Integrity Processing Unit 20 shown in FIG. 1 .

FIG. 10A is a schematic block diagram of another embodiment of adispersed storage network that includes a dispersed storage (DS)processing module 100 and a set of DS units including DS units 102-1,102-2, 102-3, 102-4 and 102-5. The DS processing module may be part of aDS processing unit 16. The DS units may be DS units 36 described above.The set of DS units includes at least a pillar width number of DS unitswhere the pillar width number is in accordance with dispersed storageerror coding parameters of a dispersed storage error coding function.For example, the set of DS units may include at least five DS units102-1, 102-2, 102-3, 102-4 and 102-5 when the pillar width is five. Ofcourse, these are merely examples, and the number of DS units used inthe system could differ, as could the width threshold.

The network shown in FIG. 10A may function to store data as a set ofencoded data slices in the set of DS units including DS units 102-1,102-2, 102-3, 102-4 and 102-5 as part of a write operation. The writeoperation may include a write initialize phase, a write commit phase,and a write finalize phase of a three-phase write function. For example,DS processing module 100 may encode the data (e.g., a data segment)using a dispersed storage error coding function in accordance withdispersed storage error coding parameters, so as to produce a set ofencoded data slices. DS processing module 100 may then generate a set ofwrite slice requests 104-1, 104-2, 104-3, 104-4 and 104-5 that mayinclude the set of encoded data slices, and may include a revisionnumber or revision level. DS processing module 100 may then output theset of write slice requests 104-1, 104-2, 104-3, 104-4 and 104-5 to DSunits 102-1, 102-2, 102-3, 102-4 and 102-5. DS processing module 100 mayalso receive one or more write slice response 106-1, 106-2, 106-3,106-4, 106-5 from at least one some of the set of DS units including DSunits 102-1, 102-2, 102-3, 102-4 and 102-5. This receiving could occurwithin a time period for example. A write slice response may include astatus code indicating whether the write succeeded or if a conflicterror exists. DS processing module 100 may determine that a write sliceresponse is favorable when the status code indicates that the writesucceeded. DS processing module 100 may also determine whether a writethreshold number of favorable write responses has been received, forexample within the time period, and/or whether one or more conflicterrors have occurred.

When the write threshold number of favorable write responses has notbeen received within a time period, for example, DS processing module100 may determine whether to wait for another time period or toimmediately initiate a retry sequence including before determining thatless than the write number of favorable write responses will bereceived. The determining may be based on one or more of a retryindicator, a query, a lookup, a response time history record, a numberof non-responses, a number of favorable responses, and a number ofunfavorable responses. For example, DS processing module 100 maydetermine to wait when receiving three favorable write responses 106-1,106-2 and 106-3 from a first group of DS units 102-1, 102-2 and 102-3,and write processing information including a conflict response 106-4(e.g., an unfavorable write response) from DS unit 102-4, andnon-response 106-5 (e.g. response 106-5 is received after a first timeperiod (slow response) or not at all) regarding DS unit 102-5 when thewrite threshold is four and a response time history record indicatesthat DS unit 102-5 typically responds during a second time period (DSunit 102-4 and 102-5 being at least part of a second group of DS units).Write processing information may include conflict status, conflictresolution (e.g. in a conflict situation, how fast the conflict can beresolved) and write response times. As another example, DS processingmodule 100 may determine to retry immediately, for example using retrywrite slice requests (which may include resending the entire set ofwrite slice requests), when receiving three favorable write responses106-1, 106-2 and 106-3 from DS units 102-1, 102-2 and 102-3, unfavorableconflict response 106-4 from DS unit 102-4, and non-response 106-5 fromDS unit 102-5 when the write threshold is four and a retry indicatorindicates to retry writing the set of encoded data slices whenresolution of an unfavorable write response may be possible due to aconflict.

When determining whether wait or retry DS processing module 100 mayoptionally determine whether to modify the set of retry write slicerequests 104-1, 104-2, 104-3, 104-4 and 104-5 to include a differentrevision number or revision level. The determining may be based on oneor more of an error indicator of the write responses, a write typeindicator, a lookup, and a predetermination. For example, DS processingmodule 100 may determine to modify the set of write slice requests104-1, 104-2, 104-3, 104-4 and 104-5 to include a different revisionnumber when one or more write responses 106-1, 106-2, 106-3, 106-4 and106-5 include an unfavorable conflict response due to a transactionconflict, and resolution of at least one transaction conflict mayproduce a write threshold number of favorable write responses during aretry sequence. When determining whether to modify the set of writeslice requests DS processing module 100 may optionally generate amodified set of write slice requests that includes the differentrevision number. The generating may include generating the differentrevision number to include generating and outputting a set of read slicerequests to the set of DS units, receiving a set of read slice responsesthat includes a current revision number, and incrementing the currentrevision number by one to produce the different revision number. DSprocessing module 100 may also optionally output the modified set ofwrite slice requests to the set of DS units. The functionality discussedabove may be utilized to analyze subsequent write slice responses anddetermine next steps thereafter.

One benefit of this approach is that in the event DSN operations areheld up due to uncertainty of success, for example due to a very slow torespond unit, it may be faster to retry an operation then to await theresult of the slow DS unit(s). According to one example, a flag may bepassed in by the requester to indicate whether or not the write isretriable (e.g., in an index node update, or region header update). Insuch a case, the DS processing unit may give up its attempt to writeentirely, and immediately try again with a new revision number. Retryingmay occur even if the operation would have eventually succeeded. As anexample, in a system with width=8, decode threshold=5, and writethreshold=6, and one DS unit is twenty minutes behind, if there are twoconflicts the DS processing unit would normally wait on the result ofthe slow store before it can make a determination of whether or not tocommit the result or send an undo or rollback request and try again. Inthis case, it may be much faster to simply retry the write, so that itsucceeds on the two stores there was previously a conflict, thus notneeding to wait on the very slow store.

FIG. 10B is a flowchart illustrating an example of storing data. Themethod begins at step 108 where a DS processing module (e.g., of adispersed storage (DS) processing module of a DS processing unit of adispersed storage network) generates a set of write slice requests thatmay include a set of encoded data slices and a revision number. Thegenerating may include generating the revision number based on aprevious revision number. The method continues at step 110 where theprocessing module outputs or sends the set of write slice requests to aset of DS units. The method continues at step 112 where the processingmodule receives one or more write slice responses, for example within atime period.

The method continues at step 114 where the processing module determineswhether the one or more write slice responses includes less than a writethreshold number of favorable write slice responses. The methodcontinues at step 116 wherein when the one or more write slice responsesincludes less than a write threshold number of favorable write sliceresponses, for example within a given time period, the processing moduledetermines whether to retry before determining less than a thresholdnumber of favorable write responses will be received. When retrying, themethod continues at an optional step 118 where the processing moduledetermines whether to modify the write slice requests. When optionallymodifying the write slice requests, the method continues at step 120where the processing module updates the write slice requests to producea set of modified write slice requests that includes a differentrevision number, and at step 122 where the processing module outputs orsends the set of modified write slice requests to the set of DS units.The method loops back to step 112 where the processing module receivesone or more write slice responses, for example within another timeperiod. In the event that the write slice requests are not modified, theprocess module may roll back the previous write slice requests and retrystoring the same set of encoded data slices, for example withoutchanging the revision number.

As may be used herein, the terms “substantially” and “approximately”provides an industry-accepted tolerance for its corresponding termand/or relativity between items. Such an industry-accepted toleranceranges from less than one percent to fifty percent and corresponds to,but is not limited to, component values, integrated circuit processvariations, temperature variations, rise and fall times, and/or thermalnoise. Such relativity between items ranges from a difference of a fewpercent to magnitude differences. As may also be used herein, theterm(s) “configured to”, “operably coupled to”, “coupled to”, and/or“coupling” includes direct coupling between items and/or indirectcoupling between items via an intervening item (e.g., an item includes,but is not limited to, a component, an element, a circuit, and/or amodule) where, for an example of indirect coupling, the intervening itemdoes not modify the information of a signal but may adjust its currentlevel, voltage level, and/or power level. As may further be used herein,inferred coupling (i.e., where one element is coupled to another elementby inference) includes direct and indirect coupling between two items inthe same manner as “coupled to”. As may even further be used herein, theterm “configured to”, “operable to”, “coupled to”, or “operably coupledto” indicates that an item includes one or more of power connections,input(s), output(s), etc., to perform, when activated, one or more itscorresponding functions and may further include inferred coupling to oneor more other items. As may still further be used herein, the term“associated with”, includes direct and/or indirect coupling of separateitems and/or one item being embedded within another item.

As may be used herein, the term “compares favorably”, indicates that acomparison between two or more items, signals, etc., provides a desiredrelationship. For example, when the desired relationship is that signalA has a greater magnitude than signal B, a favorable comparison may beachieved when the magnitude of signal A is greater than that of signal Bor when the magnitude of signal B is less than that of signal A. As maybe used herein, the term “compares unfavorably”, indicates that acomparison between two or more items, signals, etc., fails to providethe desired relationship.

As may also be used herein, the terms “processing module”, “processingcircuit”, “processor”, and/or “processing unit” may be a singleprocessing device or a plurality of processing devices. Such aprocessing device may be a microprocessor, micro-controller, digitalsignal processor, microcomputer, central processing unit, fieldprogrammable gate array, programmable logic device, state machine, logiccircuitry, analog circuitry, digital circuitry, and/or any device thatmanipulates signals (analog and/or digital) based on hard coding of thecircuitry and/or operational instructions. The processing module,module, processing circuit, and/or processing unit may be, or furtherinclude, memory and/or an integrated memory element, which may be asingle memory device, a plurality of memory devices, and/or embeddedcircuitry of another processing module, module, processing circuit,and/or processing unit. Such a memory device may be a read-only memory,random access memory, volatile memory, non-volatile memory, staticmemory, dynamic memory, flash memory, cache memory, and/or any devicethat stores digital information. Note that if the processing module,module, processing circuit, and/or processing unit includes more thanone processing device, the processing devices may be centrally located(e.g., directly coupled together via a wired and/or wireless busstructure) or may be distributedly located (e.g., cloud computing viaindirect coupling via a local area network and/or a wide area network).Further note that if the processing module, module, processing circuit,and/or processing unit implements one or more of its functions via astate machine, analog circuitry, digital circuitry, and/or logiccircuitry, the memory and/or memory element storing the correspondingoperational instructions may be embedded within, or external to, thecircuitry comprising the state machine, analog circuitry, digitalcircuitry, and/or logic circuitry. Still further note that, the memoryelement may store, and the processing module, module, processingcircuit, and/or processing unit executes, hard coded and/or operationalinstructions corresponding to at least some of the steps and/orfunctions illustrated in one or more of the Figures. Such a memorydevice or memory element can be included in an article of manufacture.

One or more embodiments have been described above with the aid of methodsteps illustrating the performance of specified functions andrelationships thereof. The boundaries and sequence of these functionalbuilding blocks and method steps have been arbitrarily defined hereinfor convenience of description. Alternate boundaries and sequences canbe defined so long as the specified functions and relationships areappropriately performed. Any such alternate boundaries or sequences arethus within the scope and spirit of the claims. Further, the boundariesof these functional building blocks have been arbitrarily defined forconvenience of description. Alternate boundaries could be defined aslong as the certain significant functions are appropriately performed.Similarly, flow diagram blocks may also have been arbitrarily definedherein to illustrate certain significant functionality.

To the extent used, the flow diagram block boundaries and sequence couldhave been defined otherwise and still perform the certain significantfunctionality. Such alternate definitions of both functional buildingblocks and flow diagram blocks and sequences are thus within the scopeand spirit of the claims. One of average skill in the art will alsorecognize that the functional building blocks, and other illustrativeblocks, modules and components herein, can be implemented as illustratedor by discrete components, application specific integrated circuits,processors executing appropriate software and the like or anycombination thereof.

In addition, a flow diagram may include a “start” and/or “continue”indication. The “start” and “continue” indications reflect that thesteps presented can optionally be incorporated in or otherwise used inconjunction with other routines. In this context, “start” indicates thebeginning of the first step presented and may be preceded by otheractivities not specifically shown. Further, the “continue” indicationreflects that the steps presented may be performed multiple times and/ormay be succeeded by other activities not specifically shown. Further,while a flow diagram indicates a particular ordering of steps, otherorderings are likewise possible provided that the principles ofcausality are maintained.

The one or more embodiments are used herein to illustrate one or moreaspects, one or more features, one or more concepts, and/or one or moreexamples. A physical embodiment of an apparatus, an article ofmanufacture, a machine, and/or of a process may include one or more ofthe aspects, features, concepts, examples, etc. described with referenceto one or more of the embodiments discussed herein. Further, from Figureto Figure, the embodiments may incorporate the same or similarly namedfunctions, steps, modules, etc. that may use the same or differentreference numbers and, as such, the functions, steps, modules, etc. maybe the same or similar functions, steps, modules, etc. or differentones.

Unless specifically stated to the contra, signals to, from, and/orbetween elements in a figure of any of the figures presented herein maybe analog or digital, continuous time or discrete time, and single-endedor differential. For instance, if a signal path is shown as asingle-ended path, it also represents a differential signal path.Similarly, if a signal path is shown as a differential path, it alsorepresents a single-ended signal path. While one or more particulararchitectures are described herein, other architectures can likewise beimplemented that use one or more data buses not expressly shown, directconnectivity between elements, and/or indirect coupling between otherelements as recognized by one of average skill in the art.

The term “module” is used in the description of one or more of theembodiments. A module implements one or more functions via a device suchas a processor or other processing device or other hardware that mayinclude or operate in association with a memory that stores operationalinstructions. A module may operate independently and/or in conjunctionwith software and/or firmware. As also used herein, a module may containone or more sub-modules, each of which may be one or more modules.

As may further be used herein, a computer readable memory includes oneor more memory elements. A memory element may be a separate memorydevice, multiple memory devices, or a set of memory locations within amemory device. Such a memory device may be a read-only memory, randomaccess memory, volatile memory, non-volatile memory, static memory,dynamic memory, flash memory, cache memory, and/or any device thatstores digital information. The memory device may be in a form a solidstate memory, a hard drive memory, cloud memory, thumb drive, servermemory, computing device memory, and/or other physical medium forstoring digital information. A computer readable memory/storage medium,as used herein, is not to be construed as being transitory signals perse, such as radio waves or other freely propagating electromagneticwaves, electromagnetic waves propagating through a waveguide or othertransmission media (e.g., light pulses passing through a fiber-opticcable), or electrical signals transmitted through a wire.

While particular combinations of various functions and features of theone or more embodiments have been expressly described herein, othercombinations of these features and functions are likewise possible. Thepresent disclosure is not limited by the particular examples disclosedherein and expressly incorporates these other combinations.

What is claimed is:
 1. A method for execution by a computing device of astorage network, comprising: receiving a write request for a dataobject; determining a plurality of data regions for the data object;determining storage identification information for each data region ofthe plurality of data regions; generating a storage table for the dataobject that includes information sufficient to identify each data regionof the plurality of data regions; for a first data region of theplurality of data regions: dividing the first data region into aplurality of data segments; dispersed error encoding the plurality ofdata segments to produce a plurality of sets of encoded data slices;sending a write request for each encoded data slice of each set ofencoded data slices of the plurality of sets of encoded data slices tothe storage network; and when at least a write threshold number of writeresponses is received for each of the plurality of sets of encoded dataslices, updating the storage table to indicate that the first dataregion is available for retrieval.
 2. The method of claim 1, furthercomprising: determining whether the data object is a very large dataobject; and when the data object is not a very large data object,determining to store the data object in a single data region.
 3. Themethod of claim 1, further comprises: searching for a preexistingstorage table and, when a preexisting storage table is not found,indicating that the write request is an initial write request.
 4. Themethod of claim 1 further comprises: for a second data region of theplurality of data regions: dividing the second data region of theplurality of data regions into a second plurality of data segments;dispersed error encoding the second plurality of data segments toproduce a second plurality of sets of encoded data slices; sending awrite request for each encoded data slice of each set of the secondplurality of sets of encoded data slices to the storage network; andwhen at least a write threshold number of write responses is receivedfor each of the second plurality of sets of encoded data slices, updatethe storage table to indicate that the second data region is availablefor retrieval.
 5. The method of claim 4 further comprises: generating atransaction number for writing one or more data regions of the pluralityof data regions to the storage network; and when the transaction numberincludes at least two data regions of the plurality of data regions: fora first one of the at least two data regions: dividing the first one ofthe at least two data regions into the plurality of data segments of thefirst one of the at least two data regions; and dispersed error encodingthe plurality of data segments of the first one of the at least two dataregions to produce a first plurality of sets of encoded data slices; fora second one of the at least two data regions: dividing the second oneof the at least two data regions into a plurality of data segments ofthe second one of the at least two data regions; and dispersed errorencoding the plurality of data segments of the second one of the atleast two data regions to produce a second plurality of sets of encodeddata slices; sending one or more write requests, each of the one or morewrite requests including the transaction number to storage units of thestorage network; and when the at least a write threshold number of writeresponses is received for each of the first and second plurality of setsof encoded data slices, updating the data object storage tracking tableto indicate that the first one and the second one of the at least twodata regions are available.
 6. The method of claim 1 further comprises:determining whether the write request is for editing the data object;and when the write request is for the editing the data object:identifying one of the plurality of data regions being edited based onthe write request to provide an identified data region; updating thestorage table to indicate that the identified data region isunavailable; dispersed error encoding one or more edited data segmentsof a plurality of data segments of the data region to produce one ormore sets of edited encoded data slices; sending updated write requestsregarding storing the one or more sets of edited encoded data slices tothe storage network; and when the at least a write threshold number ofwrite responses is received for each of the one or more sets of editedencoded data slices, updating the storage table to indicate that theidentified data region is available.
 7. The method of claim 1 furthercomprises: generating a mapping of the plurality of data regionsassociated with the data object; and storing the mapping in at least oneof: a local memory of at least one computing device of the storagenetwork.
 8. The method of claim 1 further comprises: dispersed errorencoding the storage table to produce a set of encoded table slices; andsending a write request for the set of encoded table slices to one ormore storage units associated with the storage network.
 9. The method ofclaim 8 further comprises: determining whether the storage table is tobe updated; and when the storage table is to be updated: retrieving atleast a decode threshold number of encoded table slices of the set ofencoded table slices; decoding the at least a decode threshold number ofencoded table slices to recapture the storage table; updating thestorage table to produce an updated storage table; dispersed errorencoding the updated storage table to produce a set of updated tableslices; and sending a write request for the set of updated table slicesto one or more storage units associated with the storage network. 10.The method of claim 1 further comprises: determining whether the writerequest is for editing the data object; and when the write request isfor the editing the data object: revising one or more of the pluralityof data regions; and deleting the one or more of the plurality of dataregions.
 11. A computing device of a storage network comprises: a firstmodule, when operable within the computing device, causes the computingdevice to: receive a write request for a data object; and determinewhether the write request is an initial write request for the dataobject; a second module, when operable within the computing device,causes the computing device to: when the write request is an initialwrite request: divide the data object into a plurality of data regions;generate a storage table that includes a section for identifying, ifany, one or more data regions of the plurality of data regions that areavailable for storage; and for a first data region of the plurality ofdata regions: divide the first data region of the plurality of dataregions into a plurality of data segments; dispersed error encode theplurality of data segments to produce a plurality of sets of encodeddata slices; send write requests to storage units of the storagenetwork; and when at least a write threshold number of write responsesis received for each of the plurality of sets of encoded data slices,update the storage table to indicate that the first data region isavailable for retrieval.
 12. The computing device of claim 11, whereinthe first module functions to determine whether the write request is theinitial write request for the data object based at least one of:information associated with the write request; and a search of one ormore preexisting storage tables.
 13. The computing device of claim 11,wherein the second module further functions to cause the computingdevice to: for a second data region of the plurality of data regions:divide the second data region of the plurality of data regions into aplurality of data segments of the second data region; dispersed errorencode the plurality of data segments of the second data region toproduce a second plurality of sets of encoded data slices; send writerequests regarding storing the second plurality of sets of encoded dataslices to the storage units; and when at least a write threshold numberof write responses is received for each of the second plurality of setsof encoded data slices, update the storage table to indicate that thesecond data region is available.
 14. The computing device of claim 11further comprises: the second module further functions to cause thecomputing device to: generate a transaction number for writing the oneor more data regions of the plurality of data regions to the storageunits; and when the transaction number includes at least two dataregions of the plurality of data regions: for a first one of the atleast two data regions: divide the first one of the at least two dataregions into the plurality of data segments of the first one of the atleast two data regions; and dispersed error encode the plurality of datasegments of the first one of the at least two data regions to produce afirst plurality of sets of encoded data slices; for a second one of theat least two data regions: divide the second one of the at least twodata regions into a plurality of data segments of the second one of theat least two data regions; and dispersed error encode the plurality ofdata segments of the second one of the at least two data regions toproduce a second plurality of sets of encoded data slices; send writerequests, which include the transaction number, regarding storing thefirst and second plurality of sets of encoded data slices to the storageunits; and when the at least a write threshold number of write responsesis received for each of the first and second plurality of sets ofencoded data slices, update the storage table to indicate that the firstone and the second one of the at least two data regions are available.15. The computing device of claim 11, wherein the second module furtherfunctions to cause the computing device to: determine whether the writerequest is for the editing the data object; and when the write requestis for the editing the data object: identify one of the plurality ofdata regions being edited based on the write request to provide anidentified data region; update the storage table to indicate that theidentified data region is unavailable; dispersed error encode one ormore edited data segments of a plurality of data segments of the dataregion to produce one or more sets of edited encoded data slices; andsend updated write requests regarding storing the one or more sets ofedited encoded data slices to the storage units.
 16. The computingdevice of claim 11, wherein the second module further functions to causethe computing device to: generate a mapping of the plurality of dataregions associated with the data object; and store the mapping in atleast one of: a local memory of at least one computing device of thestorage network.
 17. The computing device of claim 11, wherein thesecond module further functions to cause the computing device to:dispersed error encode the storage table to produce a set of encodedtable slices; and write the set of encoded table slices to at least someof the storage units for storage therein.
 18. The computing device ofclaim 17, wherein the second module further functions to cause thecomputing device to: determine whether the storage table is to beupdated; and when the storage table is to be updated: retrieve at leasta decode threshold number of encoded table slices of the set of encodedtable slices; decode the at least a decode threshold number of encodedtable slices to recapture the storage table; and update the storagetable to produce an updated storage table.
 19. The computing device ofclaim 11, wherein the second module is configured to at least one of:revise one or more of the plurality of data regions; and delete the oneor more of the plurality of data regions.
 20. A method for execution bya computing device of a storage network, comprising: receiving a writerequest for a large data object, wherein a large data object is acluster of smaller data objects; determining a plurality of data regionsfor storing the large data object; dividing the data object between theplurality of data regions; determining storage identificationinformation for each data region of the plurality of data regions;generating a storage table for the large data object that includesinformation sufficient to identify each data region of the plurality ofdata regions; for a first data region of the plurality of data regions:divide the first data region into a plurality of data segments; dispersestorage error encode the plurality of data segments to produce aplurality of sets of encoded data slices; send a write request for eachencoded data slice of each set of encoded data slices of the pluralityof sets of encoded data slices to the storage network; and when at leasta write threshold number of write responses is received for each of theplurality of sets of encoded data slices, update the storage table toindicate that the first data region is available for retrieval.